SVM kernal Indepth Intution and Implementation

For this we can not draw the bestfit line ,so we use SVM kernel trick to do !

Dividing the Independent and Dependent Data

Using train_test_split to train and test

When we use linear Kenrnel we got .45 accuracy, Now we will train our model with kernel as poly (if we get low accuracy_score then go for other kernels)

------>Refer notes for clear undestanding<---------

Polynomial Kernal

k(x,y) = (x**T y + c)**d

Independent and dependent variables

For 3D use plotly